[MLU]add mlu kernel for where_index op (#43720)

paddle/fluid/operators/mlu/mlu_baseop.cc

@@ -4175,15 +4175,31 @@ MLUCnnlDCNDesc::~MLUCnnlDCNDesc() {
 /* static */ void MLUCnnl::Where(const ExecutionContext& ctx,
                                  const cnnlTensorDescriptor_t x_desc,
                                  const void* x,
-                                 const uint32_t* strides,
-                                 const uint32_t* index,
+                                 const cnnlTensorDescriptor_t num_true_desc,
+                                 const void* num_true,
+                                 const bool as_tuple,
                                  const cnnlTensorDescriptor_t y_desc,
-                                 int* y,
-                                 const bool as_tuple) {
+                                 void* y) {
   cnnlHandle_t handle = GetHandleFromCTX(ctx);
-
+  size_t workspace_size;
   PADDLE_ENFORCE_MLU_SUCCESS(
-      cnnlWhere(handle, x_desc, x, strides, index, y_desc, y, as_tuple));
+      cnnlGetWhereWorkspaceSize(handle, num_true_desc, &workspace_size));
+
+  auto& dev_ctx = GetDevCtxFromCTX(ctx);
+  Tensor workspace = ctx.AllocateTmpTensor<int8_t, MLUDeviceContext>(
+      {static_cast<int64_t>(workspace_size)}, dev_ctx);
+  void* workspace_ptr = workspace.mutable_data(ctx.GetPlace());
+
+  PADDLE_ENFORCE_MLU_SUCCESS(cnnlWhere_v2(handle,
+                                          x_desc,
+                                          x,
+                                          num_true_desc,
+                                          num_true,
+                                          as_tuple,
+                                          workspace_ptr,
+                                          workspace_size,
+                                          y_desc,
+                                          y));
 }
 
 /* static */ void MLUCnnl::InTopK(const ExecutionContext& ctx,

paddle/fluid/operators/mlu/mlu_baseop.h

@@ -1607,12 +1607,11 @@ class MLUCnnl {
   static void Where(const ExecutionContext& ctx,
                     const cnnlTensorDescriptor_t x_desc,
                     const void* x,
-                    const uint32_t* strides,
-                    const uint32_t* index,
+                    const cnnlTensorDescriptor_t num_true_desc,
+                    const void* num_true,
+                    const bool as_tuple,
                     const cnnlTensorDescriptor_t y_desc,
-                    int* y,
-                    const bool as_tuple);
-
+                    void* y);
   static void Conv2D(const ExecutionContext& ctx,
                      const cnnlConvolutionDescriptor_t conv_desc,
                      const cnnlDataType_t tensor_dtype,

paddle/fluid/operators/where_index_op_mlu.cc

+/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include <vector>
+
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/operators/mlu/mlu_baseop.h"
+
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+
+template <typename T>
+class MLUWhereIndexKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto* condition = context.Input<Tensor>("Condition");
+    auto* out = context.Output<Tensor>("Out");
+    auto dims = condition->dims();
+    const int rank = dims.size();
+    std::vector<int> true_num = {0};
+    std::vector<T> vec_condition;
+    paddle::framework::TensorToVector(
+        *condition, context.device_context(), &vec_condition);
+    int vec_con_size = vec_condition.size();
+    for (int i = 0; i < vec_con_size; ++i) {
+      if (vec_condition[i] > 0) true_num[0]++;
+    }
+
+    out->Resize(phi::make_ddim({true_num[0], rank}));
+    out->mutable_data<int64_t>(context.GetPlace());
+    auto& dev_ctx = context.template device_context<MLUDeviceContext>();
+    framework::Tensor out_int32 =
+        context.AllocateTmpTensor<int32_t, MLUDeviceContext>(out->dims(),
+                                                             dev_ctx);
+    Tensor num_true;
+    paddle::framework::TensorFromVector(
+        true_num, context.device_context(), &num_true);
+    num_true.mutable_data<int>(context.GetPlace());
+    bool as_tuple = false;
+    MLUCnnlTensorDesc con_desc(*condition);
+    MLUCnnlTensorDesc num_true_desc(num_true);
+    MLUCnnlTensorDesc out_int32_desc(out_int32);
+    MLUCnnlTensorDesc out_desc(*out);
+    MLUCnnl::Where(context,
+                   con_desc.get(),
+                   GetBasePtr(condition),
+                   num_true_desc.get(),
+                   GetBasePtr(&num_true),
+                   as_tuple,
+                   out_int32_desc.get(),
+                   GetBasePtr(&out_int32));
+    cnnlCastDataType_t cast_type = GetCastDataType(VT::INT32, VT::INT64);
+    MLUCnnl::Cast(context,
+                  cast_type,
+                  out_int32_desc.get(),
+                  GetBasePtr(&out_int32),
+                  out_desc.get(),
+                  GetBasePtr(out));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_MLU_KERNEL(where_index,
+                       ops::MLUWhereIndexKernel<int>,
+                       ops::MLUWhereIndexKernel<bool>,
+                       ops::MLUWhereIndexKernel<float>);

python/paddle/fluid/tests/unittests/mlu/test_where_index_op_mlu.py

+#   Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import sys
+
+sys.path.append("..")
+import unittest
+import numpy as np
+from op_test import OpTest
+import paddle.fluid.core as core
+from paddle.fluid.op import Operator
+import paddle.fluid as fluid
+from paddle.fluid import Program, program_guard
+import paddle
+
+paddle.enable_static()
+
+
+class TestWhereIndexOp(OpTest):
+
+    def setUp(self):
+        self.op_type = "where_index"
+        self.place = paddle.device.MLUPlace(0)
+        self.__class__.use_mlu = True
+        self.init_config()
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+    def init_config(self):
+        self.inputs = {
+            'Condition': np.array([True, False, True]),
+        }
+
+        self.outputs = {'Out': np.array([[0], [2]], dtype='int64')}
+
+
+class TestAllFalse(unittest.TestCase):
+
+    def setUp(self):
+        self.op_type = "where_index"
+        self.place = paddle.device.MLUPlace(0)
+        self.__class__.use_mlu = True
+        self.init_config()
+
+    def check_with_place(self, place):
+        scope = core.Scope()
+        condition = scope.var('Condition').get_tensor()
+        condition.set(self.cond_data, place)
+
+        out = scope.var("Out").get_tensor()
+        out.set(np.full(self.shape, 0).astype('int64'), place)
+
+        op = Operator("where_index", Condition="Condition", Out="Out")
+        op.run(scope, place)
+
+        out_array = np.array(out)
+        self.assertTrue((out_array == self.out_data).all())
+
+    def init_config(self):
+        self.cond_data = np.array([False, False, False])
+        self.shape = (3, 1)
+        self.out_data = np.array([], dtype='int64')
+
+    def test_all_false(self):
+        self.check_with_place(self.place)
+
+
+class TestRank2(TestWhereIndexOp):
+
+    def init_config(self):
+        self.inputs = {
+            'Condition': np.array([[True, False], [False, True]]),
+        }
+
+        self.outputs = {'Out': np.array([[0, 0], [1, 1]], dtype='int64')}
+
+
+class TestRank3(TestWhereIndexOp):
+
+    def init_config(self):
+        self.inputs = {
+            'Condition':
+            np.array([[[True, False], [False, True]],
+                      [[False, True], [True, False]],
+                      [[False, False], [False, True]]]),
+        }
+
+        self.outputs = {
+            'Out':
+            np.array([[0, 0, 0], [0, 1, 1], [1, 0, 1], [1, 1, 0], [2, 1, 1]],
+                     dtype='int64')
+        }
+
+
+class TestWhereOpError(unittest.TestCase):
+
+    def test_api(self):
+        with program_guard(Program(), Program()):
+            cond = fluid.layers.data(name='cond', shape=[4], dtype='bool')
+            result = fluid.layers.where(cond)
+
+            exe = fluid.Executor(paddle.device.MLUPlace(0))
+            exe.run(fluid.default_startup_program())
+            cond_i = np.array([True, False, False, False]).astype("bool")
+            out = exe.run(fluid.default_main_program(), feed={'cond': cond_i})
+
+
+class TestWhereRaiseError(unittest.TestCase):
+
+    def test_errors(self):
+
+        def test_type():
+            fluid.layers.where([10])
+
+        self.assertRaises(TypeError, test_type)
+
+
+if __name__ == "__main__":
+    unittest.main()